Here, we’re just setting a few options.
knitr::opts_chunk$set(
warning = FALSE, # show warnings during codebook generation
message = FALSE, # show messages during codebook generation
error = TRUE, # do not interrupt codebook generation in case of errors,
# usually better for debugging
echo = TRUE # show R code
)
ggplot2::theme_set(ggplot2::theme_bw())
Now, we’re preparing our data for the codebook.
library(codebook)
library(formr)
# library(dplyr)
# library(labelled)
# library(ufs)
# library(GGally)
# formr_store_keys("juergen") # save my login credentials (do just once)
formr_connect(keyring = "juergen") # retreive credentials and login to formr
codebook_data <- formr_results("rbt_ext_pub") # pulls survey results
# also aggregates items with
# the same name and continuous
# numbers at the end
# to import an SPSS file from the same folder uncomment and edit the line below
# codebook_data <- rio::import("mydata.sav")
# for Stata
# codebook_data <- rio::import("mydata.dta")
# for CSV
# codebook_data <- rio::import("mydata.csv")
# omit the following lines, if your missing values are already properly labelled
codebook_data <- detect_missing(codebook_data,
only_labelled = TRUE, # only labelled values are autodetected as
# missing
negative_values_are_missing = FALSE, # negative values are missing values
ninety_nine_problems = TRUE, # 99/999 are missing values, if they
# are more than 5 MAD from the median
)
# If you are not using formr, the codebook package needs to guess which items
# form a scale. The following line finds item aggregates with names like this:
# scale = scale_1 + scale_2R + scale_3R
# identifying these aggregates allows the codebook function to
# automatically compute reliabilities.
# However, it will not reverse items automatically.
codebook_data <- detect_scales(codebook_data)
## Error in rowMeans(data[, items], na.rm = FALSE): 'x' muss numerisch sein
Create codebook
codebook(codebook_data)
Dataset name: codebook_data
The dataset has N=452 rows and 79 columns. 0 rows have no missing values on any column.
|
257 completed rows, 443 who entered any information, 9 only viewed the first page. There are 0 expired rows (people who did not finish filling out in the requested time frame). In total, there are 452 rows including unfinished and expired rows.
There were 452 unique participants, of which 257 finished filling out at least one survey.
This survey was not repeated.
The first session started on 2020-12-17 14:21:06, the last session on 2021-01-19 14:56:45.
Starting date times
People took on average 197.36 minutes (median 7.8) to answer the survey.
Duration people took for answering the survey
Distribution of values for treat
0 missing values.
| name | label | type | data_type | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| treat | calculate | character | 0 | sample(c(“cb”, “gb”, “cc”), 2, replace = F) | 1 | 0 | 1 | 3 | 0 | 2 | 2 | 0 |
| type | name | label | optional | class | showif | value | block_order | item_order |
|---|---|---|---|---|---|---|---|---|
| calculate | treat | 0 | sample(c(“cb”, “gb”, “cc”), 2, replace = F) | 1 |
| name | value |
|---|
Distribution of values for treat1
0 missing values.
| name | label | type | data_type | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| treat1 | calculate | character | 0 | treat[1] | 2 | 0 | 1 | 3 | 0 | 2 | 2 | 0 |
| type | name | label | optional | class | showif | value | block_order | item_order |
|---|---|---|---|---|---|---|---|---|
| calculate | treat1 | 0 | treat[1] | 2 |
| name | value |
|---|
Distribution of values for treat2
0 missing values.
| name | label | type | data_type | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| treat2 | calculate | character | 0 | treat[2] | 3 | 0 | 1 | 3 | 0 | 2 | 2 | 0 |
| type | name | label | optional | class | showif | value | block_order | item_order |
|---|---|---|---|---|---|---|---|---|
| calculate | treat2 | 0 | treat[2] | 3 |
| name | value |
|---|
Distribution of values for first_topic
0 missing values.
| name | label | type | data_type | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| first_topic | calculate | character | 0 | sample(c(“moral”, “robot”), 1, replace = F) | 4 | 0 | 1 | 2 | 0 | 5 | 5 | 0 |
| type | name | label | optional | class | showif | value | block_order | item_order |
|---|---|---|---|---|---|---|---|---|
| calculate | first_topic | 0 | sample(c(“moral”, “robot”), 1, replace = F) | 4 |
| name | value |
|---|
Country of residence
Distribution of values for country
195 missing values.
| name | label | type | type_options | data_type | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| country | Country of residence | select_one | haven_labelled | 0 | 68 | 195 | 0.5685841 | -999 | 1 | 4 | -2.673152 | 62.39518 | 6 | ▁▁▁▁▁▁▁▇ |
| type | type_options | name | label | optional | class | showif | value | block_order | item_order |
|---|---|---|---|---|---|---|---|---|---|
| select_one | country | Country of residence | 0 | 68 |
| name | value |
|---|---|
| England | 1 |
| Wales | 2 |
| Scotland | 3 |
| Northern Ireland | 4 |
| other | -999 |
| Item was never rendered for this user. | NA |
please specify other country
Distribution of values for country_oth
451 missing values.
| name | label | type | type_options | data_type | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| country_oth | please specify other country | text | 100 | character | 1 | country == -999 | 69 | 451 | 0.0022124 | 1 | 0 | 2 | 2 | 0 |
| type | type_options | name | label | optional | class | showif | value | block_order | item_order |
|---|---|---|---|---|---|---|---|---|---|
| text | 100 | country_oth | please specify other country | 1 | country == -999 | 69 |
| name | value |
|---|
Reliability: ωordinal [95% CI] = 0.75 [0.7;0.8].
Missing: 181.
Likert plot of scale abs1_tsm items
Distribution of scale abs1_tsm
| Dataframe: | res$dat |
| Items: | abs1_tsm_1, abs1_tsm_2, abs1_tsm_3 & abs1_tsm_4 |
| Observations: | 271 |
| Positive correlations: | 6 |
| Number of correlations: | 6 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.70 |
| Omega (hierarchical): | 0.65 |
| Revelle’s Omega (total): | 0.72 |
| Greatest Lower Bound (GLB): | 0.73 |
| Coefficient H: | 0.74 |
| Coefficient Alpha: | 0.69 |
Confidence intervals
| Omega (total): | [0.65; 0.76] |
| Coefficient Alpha: | [0.63; 0.75] |
| Ordinal Omega (total): | 0.75 |
| Ordinal Omega (hierarch.): | 0.74 |
| Ordinal Coefficient Alpha: | 0.74 |
Confidence intervals
| Ordinal Omega (total): | [0.7; 0.8] |
| Ordinal Coefficient Alpha: | [0.69; 0.79] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
2.088, 0.729, 0.706 & 0.478
| PC1 | |
|---|---|
| abs1_tsm_1 | 0.663 |
| abs1_tsm_2 | 0.756 |
| abs1_tsm_3 | 0.655 |
| abs1_tsm_4 | 0.805 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tsm_1 | 2.5572 | 3 | 0.6476 | 0.8048 | 1 | 0.0489 | 1 | 2 | 4 | 4 | -0.1015 | -0.4447 | 0.1827 | 271 | 0 | 271 |
| abs1_tsm_2 | 2.7417 | 3 | 0.7256 | 0.8518 | 1 | 0.0517 | 1 | 2 | 4 | 4 | -0.0574 | -0.757 | 0.1734 | 271 | 0 | 271 |
| abs1_tsm_3 | 2.6125 | 3 | 0.6901 | 0.8307 | 1 | 0.0505 | 1 | 2 | 4 | 4 | -0.0304 | -0.5696 | 0.1845 | 271 | 0 | 271 |
| abs1_tsm_4 | 2.8229 | 3 | 0.7389 | 0.8596 | 1 | 0.0522 | 1 | 2 | 4 | 4 | -0.3201 | -0.5394 | 0.131 | 271 | 0 | 271 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tsm_1 | The insights from the text are arbitrary. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 23 | left500 hide_label mc_width70 | 181 | 0.5995575 | 1 | 3 | 4 | 2.557196 | 0.8047624 | 5 | ▂▁▇▁▁▇▁▂ | ||||
| abs1_tsm_2 | The knowledge contained in the text cannot be generalized to other situations at all. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 23 | left500 hide_label mc_width70 | 181 | 0.5995575 | 1 | 3 | 4 | 2.741697 | 0.8518364 | 5 | ▁▁▇▁▁▇▁▅ | ||||
| abs1_tsm_3 | The opposite of the knowledge formulated in the text would be equally right/wrong. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 23 | left500 hide_label mc_width70 | 181 | 0.5995575 | 1 | 3 | 4 | 2.612546 | 0.8307010 | 5 | ▂▁▇▁▁▇▁▃ | ||||
| abs1_tsm_4 | The knowledge formulated in the text cannot claim validity for other situations. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 23 | left500 hide_label mc_width70 | 181 | 0.5995575 | 1 | 3 | 4 | 2.822878 | 0.8595825 | 5 | ▁▁▅▁▁▇▁▅ |
Reliability: ωordinal [95% CI] = 0.53 [0.44;0.62].
Missing: 181.
Likert plot of scale abs1_tsc items
Distribution of scale abs1_tsc
| Dataframe: | res$dat |
| Items: | abs1_tsc_1, abs1_tsc_2 & abs1_tsc_3 |
| Observations: | 271 |
| Positive correlations: | 1 |
| Number of correlations: | 3 |
| Percentage positive correlations: | 33 |
| Omega (total): | 0.46 |
| Omega (hierarchical): | 0.06 |
| Revelle’s Omega (total): | 0.66 |
| Greatest Lower Bound (GLB): | 0.48 |
| Coefficient H: | 0.78 |
| Coefficient Alpha: | 0.13 |
Confidence intervals
| Omega (total): | [0.36; 0.56] |
| Coefficient Alpha: | [0; 0.31] |
| Ordinal Omega (total): | 0.53 |
| Ordinal Omega (hierarch.): | 0.53 |
| Ordinal Coefficient Alpha: | 0.13 |
Confidence intervals
| Ordinal Omega (total): | [0.44; 0.62] |
| Ordinal Coefficient Alpha: | [0; 0.31] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
1.712, 0.875 & 0.413
| PC1 | |
|---|---|
| abs1_tsc_1 | 0.844 |
| abs1_tsc_2 | -0.508 |
| abs1_tsc_3 | 0.861 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tsc_1 | 2.6384 | 3 | 0.6836 | 0.8268 | 1 | 0.0502 | 1 | 2 | 4 | 4 | -0.1912 | -0.4672 | 0.1605 | 271 | 0 | 271 |
| abs1_tsc_2 | 2.3173 | 2 | 0.7137 | 0.8448 | 1 | 0.0513 | 1 | 1 | 3 | 4 | 0.123 | -0.5984 | 0.1661 | 271 | 0 | 271 |
| abs1_tsc_3 | 2.6458 | 3 | 0.637 | 0.7981 | 1 | 0.0485 | 1 | 2 | 4 | 4 | -0.1994 | -0.367 | 0.1624 | 271 | 0 | 271 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tsc_1 | The statements of the just-read text are consistent with my personal opinion on the subject. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 24 | left500 hide_label mc_width70 | 181 | 0.5995575 | 1 | 3 | 4 | 2.638376 | 0.8267762 | 5 | ▂▁▆▁▁▇▁▂ | ||||
| abs1_tsc_2 | The statements of the text excerpt I just read contradict what I myself think about the topic. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 24 | left500 hide_label mc_width70 | 181 | 0.5995575 | 1 | 2 | 4 | 2.317343 | 0.8448285 | 5 | ▃▁▇▁▁▆▁▂ | ||||
| abs1_tsc_3 | I agree with the statements I just read in the text excerpt. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 24 | left500 hide_label mc_width70 | 181 | 0.5995575 | 1 | 3 | 4 | 2.645757 | 0.7981289 | 5 | ▁▁▆▁▁▇▁▂ |
Reliability: ωordinal [95% CI] = 0.96 [0.95;0.97].
Missing: 181.
Likert plot of scale abs1_tru_exp items
Distribution of scale abs1_tru_exp
| Dataframe: | res$dat |
| Items: | abs1_tru_exp_1, abs1_tru_exp_2, abs1_tru_exp_3, abs1_tru_exp_4, abs1_tru_exp_5 & abs1_tru_exp_6 |
| Observations: | 271 |
| Positive correlations: | 15 |
| Number of correlations: | 15 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.95 |
| Omega (hierarchical): | 0.92 |
| Revelle’s Omega (total): | 0.96 |
| Greatest Lower Bound (GLB): | 0.96 |
| Coefficient H: | 0.95 |
| Coefficient Alpha: | 0.95 |
Confidence intervals
| Omega (total): | [0.94; 0.96] |
| Coefficient Alpha: | [0.94; 0.96] |
| Ordinal Omega (total): | 0.96 |
| Ordinal Omega (hierarch.): | 0.96 |
| Ordinal Coefficient Alpha: | 0.96 |
Confidence intervals
| Ordinal Omega (total): | [0.95; 0.97] |
| Ordinal Coefficient Alpha: | [0.95; 0.97] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
4.756, 0.305, 0.277, 0.256, 0.214 & 0.191
| PC1 | |
|---|---|
| abs1_tru_exp_1 | 0.869 |
| abs1_tru_exp_2 | 0.898 |
| abs1_tru_exp_3 | 0.899 |
| abs1_tru_exp_4 | 0.896 |
| abs1_tru_exp_5 | 0.886 |
| abs1_tru_exp_6 | 0.892 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tru_exp_1 | 2.9299 | 3 | 2.2432 | 1.4977 | 2 | 0.091 | 1 | 2 | 4 | 7 | 0.6136 | -0.0895 | 0.1162 | 271 | 0 | 271 |
| abs1_tru_exp_2 | 2.8303 | 3 | 2.0155 | 1.4197 | 2 | 0.0862 | 1 | 2 | 4 | 7 | 0.4518 | -0.3853 | 0.1218 | 271 | 0 | 271 |
| abs1_tru_exp_3 | 2.9225 | 3 | 2.1088 | 1.4522 | 2 | 0.0882 | 1 | 2 | 4 | 7 | 0.5087 | -0.1758 | 0.1218 | 271 | 0 | 271 |
| abs1_tru_exp_4 | 2.9557 | 3 | 2.324 | 1.5245 | 2 | 0.0926 | 1 | 2 | 4 | 7 | 0.4922 | -0.4537 | 0.1033 | 271 | 0 | 271 |
| abs1_tru_exp_5 | 3.1255 | 3 | 2.0731 | 1.4398 | 2 | 0.0875 | 1 | 2 | 4 | 7 | 0.356 | -0.3301 | 0.1144 | 271 | 0 | 271 |
| abs1_tru_exp_6 | 3.0627 | 3 | 2.0516 | 1.4323 | 2 | 0.087 | 1 | 2 | 4 | 7 | 0.3767 | -0.3026 | 0.1199 | 271 | 0 | 271 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tru_exp_1 | rating_button | 1,7,1 | haven_labelled | 1. 1: competent, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: incompetent, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 2.929889 | 1.497736 | 8 | ▆▇▇▆▁▂▂▁ | ||||
| abs1_tru_exp_2 | rating_button | 1,7,1 | haven_labelled | 1. 1: intelligent, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unintelligent, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 2.830258 | 1.419692 | 8 | ▇▇▆▇▁▂▁▁ | ||||
| abs1_tru_exp_3 | rating_button | 1,7,1 | haven_labelled | 1. 1: well educated, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: poorly educated, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 2.922509 | 1.452167 | 8 | ▆▇▆▇▁▂▁▁ | ||||
| abs1_tru_exp_4 | rating_button | 1,7,1 | haven_labelled | 1. 1: professional, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unprofessional, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 2.955720 | 1.524453 | 8 | ▇▇▆▇▁▃▂▁ | ||||
| abs1_tru_exp_5 | rating_button | 1,7,1 | haven_labelled | 1. 1: experienced, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: inexperienced, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.125461 | 1.439823 | 8 | ▅▆▇▇▁▂▂▁ | ||||
| abs1_tru_exp_6 | rating_button | 1,7,1 | haven_labelled | 1. 1: qualified, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unqualified, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.062731 | 1.432343 | 8 | ▅▇▆▇▁▂▁▁ |
Reliability: ωordinal [95% CI] = 0.9 [0.88;0.92].
Missing: 181.
Likert plot of scale abs1_tru_int items
Distribution of scale abs1_tru_int
| Dataframe: | res$dat |
| Items: | abs1_tru_int_1, abs1_tru_int_2, abs1_tru_int_3 & abs1_tru_int_4 |
| Observations: | 271 |
| Positive correlations: | 6 |
| Number of correlations: | 6 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.88 |
| Omega (hierarchical): | 0.87 |
| Revelle’s Omega (total): | 0.89 |
| Greatest Lower Bound (GLB): | 0.89 |
| Coefficient H: | 0.88 |
| Coefficient Alpha: | 0.88 |
Confidence intervals
| Omega (total): | [0.85; 0.9] |
| Coefficient Alpha: | [0.85; 0.9] |
| Ordinal Omega (total): | 0.90 |
| Ordinal Omega (hierarch.): | 0.89 |
| Ordinal Coefficient Alpha: | 0.90 |
Confidence intervals
| Ordinal Omega (total): | [0.88; 0.92] |
| Ordinal Coefficient Alpha: | [0.87; 0.92] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
2.923, 0.404, 0.368 & 0.304
| PC1 | |
|---|---|
| abs1_tru_int_1 | 0.849 |
| abs1_tru_int_2 | 0.864 |
| abs1_tru_int_3 | 0.872 |
| abs1_tru_int_4 | 0.833 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tru_int_1 | 3.1365 | 3 | 2.0813 | 1.4427 | 2 | 0.0876 | 1 | 2 | 4 | 7 | 0.3108 | -0.3415 | 0.1052 | 271 | 0 | 271 |
| abs1_tru_int_2 | 3.1365 | 3 | 1.9331 | 1.3904 | 2 | 0.0845 | 1 | 2 | 4 | 7 | 0.3533 | -0.292 | 0.1162 | 271 | 0 | 271 |
| abs1_tru_int_3 | 3.369 | 4 | 1.767 | 1.3293 | 2 | 0.0807 | 1 | 2 | 5 | 7 | 0.2323 | 0.1383 | 0.1107 | 271 | 0 | 271 |
| abs1_tru_int_4 | 3.2325 | 3 | 1.9643 | 1.4015 | 2 | 0.0851 | 1 | 2 | 4 | 7 | 0.3357 | -0.0795 | 0.1162 | 271 | 0 | 271 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tru_int_1 | rating_button | 1,7,1 | haven_labelled | 1. 1: sincere, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: insincere, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.136531 | 1.442668 | 8 | ▅▆▆▇▁▂▁▁ | ||||
| abs1_tru_int_2 | rating_button | 1,7,1 | haven_labelled | 1. 1: honest, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: dishonest, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.136531 | 1.390375 | 8 | ▃▇▇▇▁▂▂▁ | ||||
| abs1_tru_int_3 | rating_button | 1,7,1 | haven_labelled | 1. 1: just, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unjust, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 4 | 7 | 3.369004 | 1.329299 | 8 | ▂▅▅▇▁▂▁▁ | ||||
| abs1_tru_int_4 | rating_button | 1,7,1 | haven_labelled | 1. 1: fair, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unfair, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.232472 | 1.401526 | 8 | ▃▅▆▇▁▂▁▁ |
Reliability: ωordinal [95% CI] = 0.9 [0.88;0.92].
Missing: 181.
Likert plot of scale abs1_tru_ben items
Distribution of scale abs1_tru_ben
| Dataframe: | res$dat |
| Items: | abs1_tru_ben_1, abs1_tru_ben_2, abs1_tru_ben_3 & abs1_tru_ben_4 |
| Observations: | 271 |
| Positive correlations: | 6 |
| Number of correlations: | 6 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.88 |
| Omega (hierarchical): | 0.85 |
| Revelle’s Omega (total): | 0.91 |
| Greatest Lower Bound (GLB): | 0.91 |
| Coefficient H: | 0.89 |
| Coefficient Alpha: | 0.88 |
Confidence intervals
| Omega (total): | [0.86; 0.9] |
| Coefficient Alpha: | [0.86; 0.9] |
| Ordinal Omega (total): | 0.9 |
| Ordinal Omega (hierarch.): | 0.9 |
| Ordinal Coefficient Alpha: | 0.9 |
Confidence intervals
| Ordinal Omega (total): | [0.88; 0.92] |
| Ordinal Coefficient Alpha: | [0.88; 0.92] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
2.953, 0.454, 0.332 & 0.262
| PC1 | |
|---|---|
| abs1_tru_ben_1 | 0.886 |
| abs1_tru_ben_2 | 0.846 |
| abs1_tru_ben_3 | 0.844 |
| abs1_tru_ben_4 | 0.859 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tru_ben_1 | 3.2841 | 3 | 1.8634 | 1.3651 | 2 | 0.0829 | 1 | 2 | 4 | 7 | 0.2052 | -0.1931 | 0.1052 | 271 | 0 | 271 |
| abs1_tru_ben_2 | 3.1697 | 3 | 1.9711 | 1.404 | 2 | 0.0853 | 1 | 2 | 4 | 7 | 0.3501 | -0.0905 | 0.1089 | 271 | 0 | 271 |
| abs1_tru_ben_3 | 3.1402 | 3 | 1.9655 | 1.4019 | 2 | 0.0852 | 1 | 2 | 4 | 7 | 0.3819 | -0.2779 | 0.1236 | 271 | 0 | 271 |
| abs1_tru_ben_4 | 3.1845 | 3 | 1.7732 | 1.3316 | 2 | 0.0809 | 1 | 2 | 4 | 7 | 0.3592 | -0.0202 | 0.1199 | 271 | 0 | 271 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tru_ben_1 | rating_button | 1,7,1 | haven_labelled | 1. 1: moral, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: immoral, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.284133 | 1.365069 | 8 | ▂▅▅▇▁▂▁▁ | ||||
| abs1_tru_ben_2 | rating_button | 1,7,1 | haven_labelled | 1. 1: ethical, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unethical, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.169742 | 1.403952 | 8 | ▃▆▆▇▁▂▁▁ | ||||
| abs1_tru_ben_3 | rating_button | 1,7,1 | haven_labelled | 1. 1: responsible, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: irresponsible, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.140221 | 1.401945 | 8 | ▃▇▆▇▁▂▁▁ | ||||
| abs1_tru_ben_4 | rating_button | 1,7,1 | haven_labelled | 1. 1: considerate, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: inconsiderate, NA. Item was never rendered for this user. |
0 | 26 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 181 | 0.5995575 | 1 | 3 | 7 | 3.184502 | 1.331631 | 8 | ▃▅▇▆▁▂▁▁ |
Reliability: ωtotal [95% CI] = 0.83 [0.8;0.86].
Missing: 181.
Likert plot of scale abs1_tch items
Distribution of scale abs1_tch
| Dataframe: | res$dat |
| Items: | abs1_tch_1, abs1_tch_2, abs1_tch_3, abs1_tch_4 & abs1_tch_5 |
| Observations: | 271 |
| Positive correlations: | 10 |
| Number of correlations: | 10 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.83 |
| Omega (hierarchical): | 0.75 |
| Revelle’s Omega (total): | 0.87 |
| Greatest Lower Bound (GLB): | 0.87 |
| Coefficient H: | 0.83 |
| Coefficient Alpha: | 0.82 |
Confidence intervals
| Omega (total): | [0.8; 0.86] |
| Coefficient Alpha: | [0; 0.19] |
(Estimates assuming ordinal level not computed, as at least one item seems to have more than 8 levels; the highest number of distinct levels is 5 and the highest range is 1004. This last number needs to be lower than 9 for the polychoric function to work. If this is unexpected, you may want to check for outliers.)
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
2.937, 0.837, 0.478, 0.387 & 0.361
| PC1 | |
|---|---|
| abs1_tch_1 | 0.759 |
| abs1_tch_2 | 0.789 |
| abs1_tch_3 | 0.775 |
| abs1_tch_4 | 0.709 |
| abs1_tch_5 | 0.798 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tch_1 | -163.6974 | 3 | 139444.0563 | 373.4221 | 2 | 22.6838 | -999 | 1 | 4 | 4 | -1.8048 | 1.2666 | 0.0867 | 271 | 0 | 271 |
| abs1_tch_2 | -196.8266 | 3 | 160723.255 | 400.903 | 2 | 24.3531 | -999 | 1 | 4 | 4 | -1.5141 | 0.2948 | 0.1218 | 271 | 0 | 271 |
| abs1_tch_3 | -281.9446 | 2 | 204833.8969 | 452.5858 | 1002 | 27.4926 | -999 | -999 | 3 | 4 | -0.9626 | -1.0814 | 0.1421 | 271 | 0 | 271 |
| abs1_tch_4 | -134.1328 | 3 | 118711.7601 | 344.5457 | 2 | 20.9297 | -999 | 1 | 4 | 4 | -2.1289 | 2.5512 | 0.0978 | 271 | 0 | 271 |
| abs1_tch_5 | -259.6974 | 2 | 194751.2859 | 441.3063 | 1002 | 26.8075 | -999 | -999 | 3 | 4 | -1.0886 | -0.8211 | 0.131 | 271 | 0 | 271 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs1_tch_1 | It is transparent which data form the basis of the study. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 29 | left500 hide_label mc_width70 | 181 | 0.5995575 | -999 | 3 | 4 | -163.6974 | 373.4221 | 6 | ▂▁▁▁▁▁▁▇ | ||||
| abs1_tch_2 | Interested parties can have a close look at the questionnaire of the described study. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 29 | left500 hide_label mc_width70 | 181 | 0.5995575 | -999 | 3 | 4 | -196.8266 | 400.9030 | 6 | ▂▁▁▁▁▁▁▇ | ||||
| abs1_tch_3 | The data collected in the study are publicly available. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 29 | left500 hide_label mc_width70 | 181 | 0.5995575 | -999 | 2 | 4 | -281.9446 | 452.5858 | 6 | ▃▁▁▁▁▁▁▇ | ||||
| abs1_tch_4 | The authors make it easy for other researchers to understand their statistical analyses. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 29 | left500 hide_label mc_width70 | 181 | 0.5995575 | -999 | 3 | 4 | -134.1328 | 344.5457 | 6 | ▁▁▁▁▁▁▁▇ | ||||
| abs1_tch_5 | If other researchers want to repeat the study, they have easy access to the questionnaires used. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 29 | left500 hide_label mc_width70 | 181 | 0.5995575 | -999 | 2 | 4 | -259.6974 | 441.3063 | 6 | ▃▁▁▁▁▁▁▇ |
Reliability: ωordinal [95% CI] = 0.66 [0.6;0.73].
Missing: 195.
Likert plot of scale abs2_tsm items
Distribution of scale abs2_tsm
| Dataframe: | res$dat |
| Items: | abs2_tsm_1, abs2_tsm_2, abs2_tsm_3 & abs2_tsm_4 |
| Observations: | 257 |
| Positive correlations: | 6 |
| Number of correlations: | 6 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.60 |
| Omega (hierarchical): | 0.54 |
| Revelle’s Omega (total): | 0.68 |
| Greatest Lower Bound (GLB): | 0.67 |
| Coefficient H: | 0.69 |
| Coefficient Alpha: | 0.60 |
Confidence intervals
| Omega (total): | [0.53; 0.68] |
| Coefficient Alpha: | [0.51; 0.68] |
| Ordinal Omega (total): | 0.66 |
| Ordinal Omega (hierarch.): | 0.64 |
| Ordinal Coefficient Alpha: | 0.65 |
Confidence intervals
| Ordinal Omega (total): | [0.6; 0.73] |
| Ordinal Coefficient Alpha: | [0.58; 0.72] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
1.843, 0.981, 0.682 & 0.495
| PC1 | |
|---|---|
| abs2_tsm_1 | 0.675 |
| abs2_tsm_2 | 0.749 |
| abs2_tsm_3 | 0.476 |
| abs2_tsm_4 | 0.775 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tsm_1 | 2.4591 | 2 | 0.5774 | 0.7599 | 1 | 0.0474 | 1 | 1 | 3 | 4 | -0.13 | -0.3704 | 0.2004 | 257 | 0 | 257 |
| abs2_tsm_2 | 2.6887 | 3 | 0.6293 | 0.7933 | 1 | 0.0495 | 1 | 2 | 4 | 4 | 0.0962 | -0.6411 | 0.1946 | 257 | 0 | 257 |
| abs2_tsm_3 | 2.4825 | 2 | 0.6882 | 0.8296 | 1 | 0.0517 | 1 | 1 | 3 | 4 | 0.0974 | -0.5299 | 0.1809 | 257 | 0 | 257 |
| abs2_tsm_4 | 2.7821 | 3 | 0.6086 | 0.7801 | 1 | 0.0487 | 1 | 2 | 4 | 4 | -0.0456 | -0.5927 | 0.1654 | 257 | 0 | 257 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tsm_1 | The insights from the text are arbitrary. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 39 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 2 | 4 | 2.459144 | 0.7598854 | 5 | ▂▁▇▁▁▇▁▁ | ||||
| abs2_tsm_2 | The knowledge contained in the text cannot be generalized to other situations at all. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 39 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 3 | 4 | 2.688716 | 0.7932756 | 5 | ▁▁▇▁▁▇▁▃ | ||||
| abs2_tsm_3 | The opposite of the knowledge formulated in the text would be equally right/wrong. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 39 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 2 | 4 | 2.482490 | 0.8295594 | 5 | ▂▁▇▁▁▇▁▂ | ||||
| abs2_tsm_4 | The knowledge formulated in the text cannot claim validity for other situations. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 39 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 3 | 4 | 2.782101 | 0.7801183 | 5 | ▁▁▆▁▁▇▁▃ |
Reliability: ωordinal [95% CI] = 0.71 [0.22;1].
Missing: 195.
Likert plot of scale abs2_tsc items
Distribution of scale abs2_tsc
| Dataframe: | res$dat |
| Items: | abs2_tsc_1, abs2_tsc_2 & abs2_tsc_3 |
| Observations: | 257 |
| Positive correlations: | 1 |
| Number of correlations: | 3 |
| Percentage positive correlations: | 33 |
| Omega (total): | 0.64 |
| Omega (hierarchical): | 0.17 |
| Revelle’s Omega (total): | 0.64 |
| Greatest Lower Bound (GLB): | 0.55 |
| Coefficient H: | 1.00 |
| Coefficient Alpha: | 0.26 |
Confidence intervals
| Omega (total): | [0.07; 1] |
| Coefficient Alpha: | [0.1; 0.42] |
| Ordinal Omega (total): | 0.71 |
| Ordinal Omega (hierarch.): | 0.71 |
| Ordinal Coefficient Alpha: | 0.26 |
Confidence intervals
| Ordinal Omega (total): | [0.22; 1] |
| Ordinal Coefficient Alpha: | [0.1; 0.42] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
1.598, 0.962 & 0.44
| PC1 | |
|---|---|
| abs2_tsc_1 | 0.876 |
| abs2_tsc_2 | -0.356 |
| abs2_tsc_3 | 0.840 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tsc_1 | 2.642 | 3 | 0.5823 | 0.7631 | 1 | 0.0476 | 1 | 2 | 4 | 4 | -0.1429 | -0.2984 | 0.1732 | 257 | 0 | 257 |
| abs2_tsc_2 | 2.2607 | 2 | 0.5841 | 0.7643 | 1 | 0.0477 | 1 | 1 | 3 | 4 | 0.2601 | -0.1982 | 0.1459 | 257 | 0 | 257 |
| abs2_tsc_3 | 2.6887 | 3 | 0.6371 | 0.7982 | 1 | 0.0498 | 1 | 2 | 4 | 4 | -0.2163 | -0.356 | 0.1556 | 257 | 0 | 257 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tsc_1 | The statements of the just-read text are consistent with my personal opinion on the subject. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 40 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 3 | 4 | 2.642023 | 0.7630791 | 5 | ▁▁▆▁▁▇▁▂ | ||||
| abs2_tsc_2 | The statements of the text excerpt I just read contradict what I myself think about the topic. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 40 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 2 | 4 | 2.260700 | 0.7642732 | 5 | ▂▁▇▁▁▅▁▁ | ||||
| abs2_tsc_3 | I agree with the statements I just read in the text excerpt. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 40 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 3 | 4 | 2.688716 | 0.7981846 | 5 | ▁▁▅▁▁▇▁▂ |
Reliability: ωordinal [95% CI] = 0.96 [0.95;0.97].
Missing: 195.
Likert plot of scale abs2_tru_exp items
Distribution of scale abs2_tru_exp
| Dataframe: | res$dat |
| Items: | abs2_tru_exp_1, abs2_tru_exp_2, abs2_tru_exp_3, abs2_tru_exp_4, abs2_tru_exp_5 & abs2_tru_exp_6 |
| Observations: | 257 |
| Positive correlations: | 15 |
| Number of correlations: | 15 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.95 |
| Omega (hierarchical): | 0.92 |
| Revelle’s Omega (total): | 0.96 |
| Greatest Lower Bound (GLB): | 0.96 |
| Coefficient H: | 0.95 |
| Coefficient Alpha: | 0.95 |
Confidence intervals
| Omega (total): | [0.94; 0.96] |
| Coefficient Alpha: | [0.94; 0.96] |
| Ordinal Omega (total): | 0.96 |
| Ordinal Omega (hierarch.): | 0.96 |
| Ordinal Coefficient Alpha: | 0.96 |
Confidence intervals
| Ordinal Omega (total): | [0.95; 0.97] |
| Ordinal Coefficient Alpha: | [0.95; 0.97] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
4.814, 0.335, 0.278, 0.245, 0.186 & 0.141
| PC1 | |
|---|---|
| abs2_tru_exp_1 | 0.880 |
| abs2_tru_exp_2 | 0.902 |
| abs2_tru_exp_3 | 0.904 |
| abs2_tru_exp_4 | 0.914 |
| abs2_tru_exp_5 | 0.899 |
| abs2_tru_exp_6 | 0.875 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tru_exp_1 | 2.8949 | 3 | 1.7897 | 1.3378 | 2 | 0.0834 | 1 | 2 | 4 | 7 | 0.4106 | -0.3593 | 0.1304 | 257 | 0 | 257 |
| abs2_tru_exp_2 | 2.8366 | 3 | 1.9888 | 1.4103 | 2 | 0.088 | 1 | 2 | 4 | 7 | 0.4614 | -0.4624 | 0.1187 | 257 | 0 | 257 |
| abs2_tru_exp_3 | 2.7432 | 3 | 1.9494 | 1.3962 | 2 | 0.0871 | 1 | 2 | 4 | 7 | 0.5624 | -0.1977 | 0.1128 | 257 | 0 | 257 |
| abs2_tru_exp_4 | 2.7315 | 3 | 1.9237 | 1.387 | 2 | 0.0865 | 1 | 2 | 4 | 7 | 0.5351 | -0.2842 | 0.1128 | 257 | 0 | 257 |
| abs2_tru_exp_5 | 2.821 | 3 | 1.71 | 1.3077 | 2 | 0.0816 | 1 | 2 | 4 | 7 | 0.3988 | -0.2843 | 0.1284 | 257 | 0 | 257 |
| abs2_tru_exp_6 | 2.9183 | 3 | 2.1925 | 1.4807 | 2 | 0.0924 | 1 | 2 | 4 | 7 | 0.4544 | -0.6173 | 0.1051 | 257 | 0 | 257 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tru_exp_1 | rating_button | 1,7,1 | haven_labelled | 1. 1: competent, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: incompetent, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 2.894942 | 1.337797 | 8 | ▅▇▆▇▁▂▁▁ | ||||
| abs2_tru_exp_2 | rating_button | 1,7,1 | haven_labelled | 1. 1: intelligent, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unintelligent, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 2.836576 | 1.410253 | 8 | ▆▇▆▇▁▂▂▁ | ||||
| abs2_tru_exp_3 | rating_button | 1,7,1 | haven_labelled | 1. 1: well educated, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: poorly educated, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 2.743191 | 1.396215 | 8 | ▇▇▇▆▁▂▁▁ | ||||
| abs2_tru_exp_4 | rating_button | 1,7,1 | haven_labelled | 1. 1: professional, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unprofessional, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 2.731517 | 1.386986 | 8 | ▇▇▆▆▁▂▁▁ | ||||
| abs2_tru_exp_5 | rating_button | 1,7,1 | haven_labelled | 1. 1: experienced, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: inexperienced, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 2.821012 | 1.307679 | 8 | ▆▇▇▇▁▁▁▁ | ||||
| abs2_tru_exp_6 | rating_button | 1,7,1 | haven_labelled | 1. 1: qualified, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unqualified, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 2.918288 | 1.480715 | 8 | ▆▇▆▆▁▂▂▁ |
Reliability: ωordinal [95% CI] = 0.92 [0.9;0.94].
Missing: 195.
Likert plot of scale abs2_tru_int items
Distribution of scale abs2_tru_int
| Dataframe: | res$dat |
| Items: | abs2_tru_int_1, abs2_tru_int_2, abs2_tru_int_3 & abs2_tru_int_4 |
| Observations: | 257 |
| Positive correlations: | 6 |
| Number of correlations: | 6 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.90 |
| Omega (hierarchical): | 0.17 |
| Revelle’s Omega (total): | 0.25 |
| Greatest Lower Bound (GLB): | 0.91 |
| Coefficient H: | 0.90 |
| Coefficient Alpha: | 0.90 |
Confidence intervals
| Omega (total): | [0.88; 0.92] |
| Coefficient Alpha: | [0.88; 0.92] |
| Ordinal Omega (total): | 0.92 |
| Ordinal Omega (hierarch.): | 0.92 |
| Ordinal Coefficient Alpha: | 0.92 |
Confidence intervals
| Ordinal Omega (total): | [0.9; 0.94] |
| Ordinal Coefficient Alpha: | [0.9; 0.94] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
3.084, 0.372, 0.276 & 0.269
| PC1 | |
|---|---|
| abs2_tru_int_1 | 0.888 |
| abs2_tru_int_2 | 0.871 |
| abs2_tru_int_3 | 0.868 |
| abs2_tru_int_4 | 0.885 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tru_int_1 | 2.9883 | 3 | 1.9569 | 1.3989 | 2 | 0.0873 | 1 | 2 | 4 | 7 | 0.4092 | -0.3059 | 0.1245 | 257 | 0 | 257 |
| abs2_tru_int_2 | 2.8794 | 3 | 1.8877 | 1.3739 | 2 | 0.0857 | 1 | 2 | 4 | 7 | 0.2282 | -0.7448 | 0.1167 | 257 | 0 | 257 |
| abs2_tru_int_3 | 3.179 | 3 | 1.7725 | 1.3314 | 2 | 0.083 | 1 | 2 | 4 | 7 | 0.2183 | -0.0663 | 0.1128 | 257 | 0 | 257 |
| abs2_tru_int_4 | 3 | 3 | 1.6484 | 1.2839 | 2 | 0.0801 | 1 | 2 | 4 | 7 | 0.1786 | -0.4366 | 0.1284 | 257 | 0 | 257 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tru_int_1 | rating_button | 1,7,1 | haven_labelled | 1. 1: sincere, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: insincere, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 2.988327 | 1.398890 | 8 | ▅▇▇▇▁▂▁▁ | ||||
| abs2_tru_int_2 | rating_button | 1,7,1 | haven_labelled | 1. 1: honest, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: dishonest, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 2.879377 | 1.373949 | 8 | ▆▆▅▇▁▂▁▁ | ||||
| abs2_tru_int_3 | rating_button | 1,7,1 | haven_labelled | 1. 1: just, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unjust, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 3.178988 | 1.331362 | 8 | ▃▅▅▇▁▂▁▁ | ||||
| abs2_tru_int_4 | rating_button | 1,7,1 | haven_labelled | 1. 1: fair, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unfair, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 3.000000 | 1.283915 | 8 | ▅▆▇▇▁▂▁▁ |
Reliability: ωtotal [95% CI] = 0.91 [not computed].
Missing: 195.
Likert plot of scale abs2_tru_ben items
Distribution of scale abs2_tru_ben
| Dataframe: | res$dat |
| Items: | abs2_tru_ben_1, abs2_tru_ben_2, abs2_tru_ben_3 & abs2_tru_ben_4 |
| Observations: | 257 |
| Positive correlations: | 6 |
| Number of correlations: | 6 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.91 |
| Omega (hierarchical): | 0.01 |
| Revelle’s Omega (total): | 0.92 |
| Greatest Lower Bound (GLB): | 0.92 |
| Coefficient H: | 0.92 |
| Coefficient Alpha: | 0.91 |
(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
3.175, 0.335, 0.279 & 0.212
| PC1 | |
|---|---|
| abs2_tru_ben_1 | 0.919 |
| abs2_tru_ben_2 | 0.868 |
| abs2_tru_ben_3 | 0.893 |
| abs2_tru_ben_4 | 0.883 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tru_ben_1 | 3.1089 | 3 | 1.8318 | 1.3535 | 2 | 0.0844 | 1 | 2 | 4 | 7 | 0.2007 | -0.2904 | 0.1089 | 257 | 0 | 257 |
| abs2_tru_ben_2 | 3.0623 | 3 | 1.8633 | 1.365 | 2 | 0.0851 | 1 | 2 | 4 | 7 | 0.184 | -0.4586 | 0.1148 | 257 | 0 | 257 |
| abs2_tru_ben_3 | 3.07 | 3 | 2.0654 | 1.4371 | 2 | 0.0896 | 1 | 2 | 4 | 7 | 0.3141 | -0.4669 | 0.1109 | 257 | 0 | 257 |
| abs2_tru_ben_4 | 3.1128 | 3 | 1.7021 | 1.3046 | 2 | 0.0814 | 1 | 2 | 4 | 6 | 0.0871 | -0.6178 | 0.1323 | 257 | 0 | 257 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tru_ben_1 | rating_button | 1,7,1 | haven_labelled | 1. 1: moral, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: immoral, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 3.108949 | 1.353452 | 8 | ▃▅▅▇▁▂▁▁ | ||||
| abs2_tru_ben_2 | rating_button | 1,7,1 | haven_labelled | 1. 1: ethical, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: unethical, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 3.062257 | 1.365026 | 8 | ▅▆▆▇▁▂▁▁ | ||||
| abs2_tru_ben_3 | rating_button | 1,7,1 | haven_labelled | 1. 1: responsible, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: irresponsible, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 7 | 3.070039 | 1.437146 | 8 | ▅▆▅▇▁▂▂▁ | ||||
| abs2_tru_ben_4 | rating_button | 1,7,1 | haven_labelled | 1. 1: considerate, 2. 2, 3. 3, 4. 4, 5. 5, 6. 6, 7. 7: inconsiderate, NA. Item was never rendered for this user. |
0 | 46 | answer_align_center left0 space_bottom_10 rating_button_label_width150 | 195 | 0.5685841 | 1 | 3 | 6 | 3.112840 | 1.304631 | 8 | ▃▆▁▇▇▁▃▁ |
Reliability: ωtotal [95% CI] = 0.94 [0.92;0.95].
Missing: 195.
Likert plot of scale abs2_tch items
Distribution of scale abs2_tch
| Dataframe: | res$dat |
| Items: | abs2_tch_1, abs2_tch_2, abs2_tch_3, abs2_tch_4 & abs2_tch_5 |
| Observations: | 257 |
| Positive correlations: | 10 |
| Number of correlations: | 10 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.94 |
| Omega (hierarchical): | 0.88 |
| Revelle’s Omega (total): | 0.96 |
| Greatest Lower Bound (GLB): | 0.96 |
| Coefficient H: | 0.94 |
| Coefficient Alpha: | 0.94 |
Confidence intervals
| Omega (total): | [0.92; 0.95] |
| Coefficient Alpha: | [0; 0.19] |
(Estimates assuming ordinal level not computed, as at least one item seems to have more than 8 levels; the highest number of distinct levels is 5 and the highest range is 1004. This last number needs to be lower than 9 for the polychoric function to work. If this is unexpected, you may want to check for outliers.)
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
3.984, 0.366, 0.32, 0.213 & 0.117
| PC1 | |
|---|---|
| abs2_tch_1 | 0.868 |
| abs2_tch_2 | 0.911 |
| abs2_tch_3 | 0.863 |
| abs2_tch_4 | 0.897 |
| abs2_tch_5 | 0.923 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tch_1 | -192.1245 | 3 | 157873.1329 | 397.3325 | 2 | 24.7849 | -999 | 1 | 4 | 4 | -1.5523 | 0.4128 | 0.1148 | 257 | 0 | 257 |
| abs2_tch_2 | -196.0389 | 2 | 160246.2329 | 400.3077 | 3 | 24.9705 | -999 | -999 | 4 | 4 | -1.5211 | 0.3161 | 0.1109 | 257 | 0 | 257 |
| abs2_tch_3 | -246.7938 | 2 | 188361.4846 | 434.0063 | 2 | 27.0726 | -999 | -999 | 4 | 4 | -1.1675 | -0.6419 | 0.1245 | 257 | 0 | 257 |
| abs2_tch_4 | -184.3268 | 3 | 153023.2365 | 391.1818 | 2 | 24.4013 | -999 | 1 | 4 | 4 | -1.6169 | 0.619 | 0.1187 | 257 | 0 | 257 |
| abs2_tch_5 | -223.3307 | 2 | 176044.98 | 419.5771 | 2 | 26.1725 | -999 | -999 | 4 | 4 | -1.3201 | -0.2593 | 0.1206 | 257 | 0 | 257 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| abs2_tch_1 | It is transparent which data form the basis of the study. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 50 | left500 hide_label mc_width70 | 195 | 0.5685841 | -999 | 3 | 4 | -192.1245 | 397.3325 | 6 | ▂▁▁▁▁▁▁▇ | ||||
| abs2_tch_2 | Interested parties can have a close look at the questionnaire of the described study. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 50 | left500 hide_label mc_width70 | 195 | 0.5685841 | -999 | 2 | 4 | -196.0389 | 400.3077 | 6 | ▂▁▁▁▁▁▁▇ | ||||
| abs2_tch_3 | The data collected in the study are publicly available. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 50 | left500 hide_label mc_width70 | 195 | 0.5685841 | -999 | 2 | 4 | -246.7938 | 434.0063 | 6 | ▂▁▁▁▁▁▁▇ | ||||
| abs2_tch_4 | The authors make it easy for other researchers to understand their statistical analyses. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 50 | left500 hide_label mc_width70 | 195 | 0.5685841 | -999 | 3 | 4 | -184.3268 | 391.1818 | 6 | ▂▁▁▁▁▁▁▇ | ||||
| abs2_tch_5 | If other researchers want to repeat the study, they have easy access to the questionnaires used. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, -999. (don’t know), NA. Item was never rendered for this user. |
0 | 50 | left500 hide_label mc_width70 | 195 | 0.5685841 | -999 | 2 | 4 | -223.3307 | 419.5771 | 6 | ▂▁▁▁▁▁▁▇ |
Reliability: ωordinal [95% CI] = 0.74 [0.69;0.8].
Missing: 195.
Likert plot of scale tsm items
Distribution of scale tsm
| Dataframe: | res$dat |
| Items: | tsm_1, tsm_2 & tsm_3 |
| Observations: | 257 |
| Positive correlations: | 3 |
| Number of correlations: | 3 |
| Percentage positive correlations: | 100 |
| Omega (total): | 0.66 |
| Omega (hierarchical): | 0.05 |
| Revelle’s Omega (total): | 0.68 |
| Greatest Lower Bound (GLB): | 0.70 |
| Coefficient H: | 0.71 |
| Coefficient Alpha: | 0.65 |
Confidence intervals
| Omega (total): | [0.59; 0.73] |
| Coefficient Alpha: | [0.58; 0.73] |
| Ordinal Omega (total): | 0.74 |
| Ordinal Omega (hierarch.): | 0.74 |
| Ordinal Coefficient Alpha: | 0.73 |
Confidence intervals
| Ordinal Omega (total): | [0.69; 0.8] |
| Ordinal Coefficient Alpha: | [0.67; 0.79] |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.
1.788, 0.721 & 0.491
| PC1 | |
|---|---|
| tsm_1 | 0.825 |
| tsm_2 | 0.795 |
| tsm_3 | 0.689 |
| mean | median | var | sd | IQR | se | min | q1 | q3 | max | skew | kurt | dip | n | NA | valid | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| tsm_1 | 3.2023 | 3 | 0.662 | 0.8136 | 1 | 0.0508 | 1 | 2 | 4 | 4 | -0.7821 | -0.0013 | 0.2023 | 257 | 0 | 257 |
| tsm_2 | 3.2335 | 3 | 0.6875 | 0.8291 | 1 | 0.0517 | 1 | 2 | 4 | 4 | -0.9154 | 0.2428 | 0.1946 | 257 | 0 | 257 |
| tsm_3 | 2.7237 | 3 | 0.8413 | 0.9173 | 1 | 0.0572 | 1 | 2 | 4 | 4 | -0.3115 | -0.6889 | 0.1284 | 257 | 0 | 257 |
Scatterplot
| name | label | type | type_options | data_type | value_labels | optional | showif | value | item_order | block_order | class | n_missing | complete_rate | min | median | max | mean | sd | n_value_labels | hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| tsm_1 | The explanations (grey text boxes) were helpful for understanding the badges (“Open Materials”, “Open Data”, “Open Code”). | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 57 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 3 | 4 | 3.202335 | 0.8136497 | 5 | ▁▁▃▁▁▇▁▇ | ||||
| tsm_2 | I read all additional explanations (grey text boxes) on the front pages. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 57 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 3 | 4 | 3.233463 | 0.8291379 | 5 | ▁▁▂▁▁▇▁▇ | ||||
| tsm_3 | The badges (“Open Materials”, “Open Data”, “Open Code”) influenced my assessment of the authors. | mc | haven_labelled | 1. fully <br />disagree, 2. , 3. , 4. fully <br />agree, NA. Item was never rendered for this user. |
0 | 57 | left500 hide_label mc_width70 | 195 | 0.5685841 | 1 | 3 | 4 | 2.723735 | 0.9172505 | 5 | ▂▁▅▁▁▇▁▃ |
The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.
{
"name": "codebook_data",
"datePublished": "2023-02-12",
"description": "The dataset has N=452 rows and 79 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.4.9000).",
"keywords": ["session", "created", "modified", "ended", "expired", "treat", "treat1", "treat2", "first_topic", "abs1_tsm_1", "abs1_tsm_2", "abs1_tsm_3", "abs1_tsm_4", "abs1_tsc_1", "abs1_tsc_2", "abs1_tsc_3", "abs1_tru_exp_1", "abs1_tru_exp_2", "abs1_tru_exp_3", "abs1_tru_exp_4", "abs1_tru_exp_5", "abs1_tru_exp_6", "abs1_tru_int_1", "abs1_tru_int_2", "abs1_tru_int_3", "abs1_tru_int_4", "abs1_tru_ben_1", "abs1_tru_ben_2", "abs1_tru_ben_3", "abs1_tru_ben_4", "abs1_tch_1", "abs1_tch_2", "abs1_tch_3", "abs1_tch_4", "abs1_tch_5", "abs2_tsm_1", "abs2_tsm_2", "abs2_tsm_3", "abs2_tsm_4", "abs2_tsc_1", "abs2_tsc_2", "abs2_tsc_3", "abs2_tru_exp_1", "abs2_tru_exp_2", "abs2_tru_exp_3", "abs2_tru_exp_4", "abs2_tru_exp_5", "abs2_tru_exp_6", "abs2_tru_int_1", "abs2_tru_int_2", "abs2_tru_int_3", "abs2_tru_int_4", "abs2_tru_ben_1", "abs2_tru_ben_2", "abs2_tru_ben_3", "abs2_tru_ben_4", "abs2_tch_1", "abs2_tch_2", "abs2_tch_3", "abs2_tch_4", "abs2_tch_5", "tsm_1", "tsm_2", "tsm_3", "country", "country_oth", "abs1_tsm", "abs1_tsc", "abs1_tru_exp", "abs1_tru_int", "abs1_tru_ben", "abs1_tch", "abs2_tsm", "abs2_tsc", "abs2_tru_exp", "abs2_tru_int", "abs2_tru_ben", "abs2_tch", "tsm"],
"@context": "http://schema.org/",
"@type": "Dataset",
"variableMeasured": [
{
"name": "session",
"@type": "propertyValue"
},
{
"name": "created",
"description": "user first opened survey",
"@type": "propertyValue"
},
{
"name": "modified",
"description": "user last edited survey",
"@type": "propertyValue"
},
{
"name": "ended",
"description": "user finished survey",
"@type": "propertyValue"
},
{
"name": "expired",
"@type": "propertyValue"
},
{
"name": "treat",
"description": "",
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "treat1",
"description": "",
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "treat2",
"description": "",
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "first_topic",
"description": "",
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tsm_1",
"description": "The insights from the text are arbitrary.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tsm_2",
"description": "The knowledge contained in the text cannot be generalized to other situations at all.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tsm_3",
"description": "The opposite of the knowledge formulated in the text would be equally right/wrong.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tsm_4",
"description": "The knowledge formulated in the text cannot claim validity for other situations.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tsc_1",
"description": "The statements of the just-read text are consistent with my personal opinion on the subject.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tsc_2",
"description": "The statements of the text excerpt I just read contradict what I myself think about the topic.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tsc_3",
"description": "I agree with the statements I just read in the text excerpt.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_exp_1",
"description": "",
"value": "1. 1: competent,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: incompetent,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_exp_2",
"description": "",
"value": "1. 1: intelligent,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unintelligent,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_exp_3",
"description": "",
"value": "1. 1: well educated,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: poorly educated,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_exp_4",
"description": "",
"value": "1. 1: professional,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unprofessional,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_exp_5",
"description": "",
"value": "1. 1: experienced,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: inexperienced,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_exp_6",
"description": "",
"value": "1. 1: qualified,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unqualified,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_int_1",
"description": "",
"value": "1. 1: sincere,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: insincere,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_int_2",
"description": "",
"value": "1. 1: honest,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: dishonest,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_int_3",
"description": "",
"value": "1. 1: just,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unjust,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_int_4",
"description": "",
"value": "1. 1: fair,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unfair,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_ben_1",
"description": "",
"value": "1. 1: moral,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: immoral,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_ben_2",
"description": "",
"value": "1. 1: ethical,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unethical,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_ben_3",
"description": "",
"value": "1. 1: responsible,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: irresponsible,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tru_ben_4",
"description": "",
"value": "1. 1: considerate,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: inconsiderate,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tch_1",
"description": "It is transparent which data form the basis of the study.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tch_2",
"description": "Interested parties can have a close look at the questionnaire of the described study.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tch_3",
"description": "The data collected in the study are publicly available.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tch_4",
"description": "The authors make it easy for other researchers to understand their statistical analyses.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tch_5",
"description": "If other researchers want to repeat the study, they have easy access to the questionnaires used.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tsm_1",
"description": "The insights from the text are arbitrary.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tsm_2",
"description": "The knowledge contained in the text cannot be generalized to other situations at all.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tsm_3",
"description": "The opposite of the knowledge formulated in the text would be equally right/wrong.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tsm_4",
"description": "The knowledge formulated in the text cannot claim validity for other situations.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tsc_1",
"description": "The statements of the just-read text are consistent with my personal opinion on the subject.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tsc_2",
"description": "The statements of the text excerpt I just read contradict what I myself think about the topic.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tsc_3",
"description": "I agree with the statements I just read in the text excerpt.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_exp_1",
"description": "",
"value": "1. 1: competent,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: incompetent,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_exp_2",
"description": "",
"value": "1. 1: intelligent,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unintelligent,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_exp_3",
"description": "",
"value": "1. 1: well educated,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: poorly educated,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_exp_4",
"description": "",
"value": "1. 1: professional,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unprofessional,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_exp_5",
"description": "",
"value": "1. 1: experienced,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: inexperienced,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_exp_6",
"description": "",
"value": "1. 1: qualified,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unqualified,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_int_1",
"description": "",
"value": "1. 1: sincere,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: insincere,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_int_2",
"description": "",
"value": "1. 1: honest,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: dishonest,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_int_3",
"description": "",
"value": "1. 1: just,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unjust,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_int_4",
"description": "",
"value": "1. 1: fair,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unfair,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_ben_1",
"description": "",
"value": "1. 1: moral,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: immoral,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_ben_2",
"description": "",
"value": "1. 1: ethical,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: unethical,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_ben_3",
"description": "",
"value": "1. 1: responsible,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: irresponsible,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tru_ben_4",
"description": "",
"value": "1. 1: considerate,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6,\n7. 7: inconsiderate,\nNA. Item was never rendered for this user.",
"maxValue": 7,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tch_1",
"description": "It is transparent which data form the basis of the study.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tch_2",
"description": "Interested parties can have a close look at the questionnaire of the described study.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tch_3",
"description": "The data collected in the study are publicly available.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tch_4",
"description": "The authors make it easy for other researchers to understand their statistical analyses.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs2_tch_5",
"description": "If other researchers want to repeat the study, they have easy access to the questionnaires used.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\n-999. (don't know),\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "tsm_1",
"description": "The explanations (grey text boxes) were helpful for understanding the badges (\"Open Materials\", \"Open Data\", \"Open Code\").",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "tsm_2",
"description": "I read all additional explanations (grey text boxes) on the front pages.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "tsm_3",
"description": "The badges (\"Open Materials\", \"Open Data\", \"Open Code\") influenced my assessment of the authors.",
"value": "1. __fully <br />disagree__,\n2. ,\n3. ,\n4. __fully <br />agree__,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": 1,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "country",
"description": "Country of residence",
"value": "1. England,\n2. Wales,\n3. Scotland,\n4. Northern Ireland,\n-999. other,\nNA. Item was never rendered for this user.",
"maxValue": 4,
"minValue": -999,
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "country_oth",
"description": "please specify other country",
"measurementTechnique": "self-report",
"@type": "propertyValue"
},
{
"name": "abs1_tsm",
"description": "4 abs1_tsm items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs1_tsc",
"description": "3 abs1_tsc items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs1_tru_exp",
"description": "6 abs1_tru_exp items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs1_tru_int",
"description": "4 abs1_tru_int items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs1_tru_ben",
"description": "4 abs1_tru_ben items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs1_tch",
"description": "5 abs1_tch items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs2_tsm",
"description": "4 abs2_tsm items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs2_tsc",
"description": "3 abs2_tsc items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs2_tru_exp",
"description": "6 abs2_tru_exp items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs2_tru_int",
"description": "4 abs2_tru_int items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs2_tru_ben",
"description": "4 abs2_tru_ben items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "abs2_tch",
"description": "5 abs2_tch items aggregated by aggregation_function",
"@type": "propertyValue"
},
{
"name": "tsm",
"description": "3 tsm items aggregated by aggregation_function",
"@type": "propertyValue"
}
]
}`